Special Issue "Machine Learning Applications in Power System Condition Monitoring"
Deadline for manuscript submissions: closed (15 December 2021) | Viewed by 8016
Interests: condition monitoring; renewable generation; rotating plant; machine learning; load forecasting; load characterization; power networks; meteorological effects; fault prognostics; fault diagnosis
I am inviting submissions for a Special Issue of Energies on the subject area of “Machine Learning Applications in Power System Condition Monitoring”. In recent years, power systems have undergone a once in a generation transformation to accommodate low carbon technologies while supporting ever higher expectations of service level. New technology and legacy plants are expected to co-exist seamlessly on networks that are being used outside of their original design specification through schemes such as dynamic rating. Condition monitoring offers a route to facilitating this but only if data can be reduced to an interpretable form, which is where machine learning offers leverage. Supporting existing domain expertise with higher resolution operational insight unlocks the investment in condition monitoring, and here the design of appropriate analytics and automation is key. Whether at generation, transmission, distribution, or end use, power assets are diverse and their performance is reflective of their health and operating environment. Accordingly, topics of interest for this Special Issue include, but are not limited to:
- Monitoring of renewable generation
- Monitoring of legacy assets
- Transmission and distribution network assets
- Prognostics for battery energy storage
- Minimal data availability
- Condition monitoring of power electronics
- Explicable machine learning
- Integration of machine learning with physics based models
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- Power networks
- Machine learning
- Power generation
- Renewable generation
- Anomaly detection
- Nuclear generation
- Model selection
- Fault diagnosis
- Power system protection
- Power quality